Hypoxia influences polysome distribution of human ribosomal protein S12 and alternative splicing of ribosomal protein mRNAs
Bibliographic record
Abstract
Ribosomes were once considered static in their composition because of their essential role in protein synthesis and kingdom-wide conservation. The existence of tolerated mutations in select ribosomal proteins (RPs), such as in Diamond-Blackfan anemia, is evidence that not all ribosome components are essential. Heterogeneity in the protein composition of eukaryotic ribosomes is an emerging concept with evidence that different pools of ribosomes exist with transcript-specificity. Here, we show that the polysome association of ribosomal proteins is altered by low oxygen (hypoxia), a feature of the tumor microenvironment, in human cells. We quantified ribosomal protein abundance in actively translating polysomes of normoxic and hypoxic HEK293 cells by tandem mass tags mass spectrometry. Our data suggest that RPS12 (eS12) is enriched in hypoxic monosomes, which increases the heavy polysome association of structured transcripts APAF-1 and XIAP. Furthermore, hypoxia induced five alternative splicing events within a subset of RP mRNAs in cell lines. One of these events in RPS24 (eS24 protein) alters the coding sequence to produce two protein isoforms that can incorporate into ribosomes. This splicing event is greatly induced in spheroids and correlates with tumor hypoxia in human prostate cancer. Our data suggest that hypoxia may influence the composition of the human ribosome through changes in RP incorporation and the production of hypoxia-specific RP isoforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".